Adaptive event-triggered prescribed performance learning synchronization for complex dynamical networks with unknown time-varying coupling strength - Fan, Aili; Li, Junmin; Li, Jinsha (Nonlinear dynamics, 2020)
In this paper, we focus on investigating the prescribed performance synchronization problems of complex dynamical networks with unknown time-varying coupling strength by learning control method. An event-triggered control protocol is designed, and a sufficient condition of synchronization is also given based on Lyapunov stability theory, which can ensure that the sates of all nodes synchronize to the specified target trajectory, and the synchronization errors meet the prescribed performance requirements. The main advantage of the protocol is not only to ensure the transient performance and convergence of synchronization errors of complex dynamic networks with unknown time-varying coupling strength, but also to avoid the continuous communication among network nodes under the event-triggered communication mechanism which can reduce the number of information updates. In addition, the Zeno behavior is avoided in communication process of the networks. At last, the effectiveness of the proposed theoretic results obtained is verified via the applications of the complex dynamical networks with Chua’s circuit and a simple pendulum dynamics.